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Constrained Modeling for Efficient Multi-objective Optimization

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Performance-Driven Surrogate Modeling of High-Frequency Structures

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Abstract

This chapter discusses the applications of performance-driven modeling framework to low-cost multi-objective design of high-frequency structures. It is a matter of fact that vast majority of practical engineering problems are multi-objective ones. Although in most practical cases various scalarization strategies are employed for the sake of simplicity (e.g., to enable application of single-objective optimization routines), at times, genuine multi-objective treatment is necessary. A typical scenario is the need for generating the best possible trade-offs between conflicting objectives, which permits comprehensive evaluation of a given structure, e.g., from the point of view of its suitability for a selected application area. Two constrained modeling methodologies, namely, the triangulation-based and nested kriging modeling techniques, are adopted for solving multi-objective design tasks, i.e., identification of the Pareto sets, in a computationally efficient manner. Real-world high-frequency design cases are considered to demonstrate the efficacy of the presented approach.

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Authors and Affiliations

  1. School of Science and Engineering, Reykjavik University, Reykjavik, Iceland

    Slawomir Koziel

  2. Faculty of Electronics, Telecommunications and Informatics, Gdansk University of Technology, Gdansk, Poland

    Anna Pietrenko-Dabrowska

Authors
  1. Slawomir Koziel
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  2. Anna Pietrenko-Dabrowska
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Koziel, S., Pietrenko-Dabrowska, A. (2020). Constrained Modeling for Efficient Multi-objective Optimization. In: Performance-Driven Surrogate Modeling of High-Frequency Structures. Springer, Cham. https://doi.org/10.1007/978-3-030-38926-0_10

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  • DOI: https://doi.org/10.1007/978-3-030-38926-0_10

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-38925-3

  • Online ISBN: 978-3-030-38926-0

  • eBook Packages: EngineeringEngineering (R0)

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